Residential Energy Consumption Prediction Based on Encoder-Decoder LSTM

Junni Su; Lide Zhou; Fengchao Chen; Zejian Qiu

doi:10.1007/978-3-031-31733-0_27

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Residential Energy Consumption Prediction Based on Encoder-Decoder LSTM

Junni Su Lide Zhou Fengchao Chen Zejian Qiu

Year: 2023 Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Pages: 319-330

DOI: 10.1007/978-3-031-31733-0_27

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Keywords:

Predictability Computer science Granularity Hyperparameter Combing Data mining Smart grid Hyperparameter optimization Metadata Process (computing) Bottleneck Artificial neural network Kalman filter Encoder Smart meter Machine learning Artificial intelligence Engineering Embedded system

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Energy Load and Power Forecasting

Physical Sciences → Engineering → Electrical and Electronic Engineering

Traffic Prediction and Management Techniques

Physical Sciences → Engineering → Building and Construction

Stock Market Forecasting Methods

Social Sciences → Decision Sciences → Management Science and Operations Research

Residential Energy Consumption Prediction Based on Encoder-Decoder LSTM

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